Revenue Calculator

Projects revenue and net profit projections for OpenClaw sub-agent monetization strategies with sensitivity and break-even analysis.

Security Scan

The skill's code, instructions, and requirements are consistent with a simple revenue-projection utility and do not request unrelated credentials or network installs.

Purpose & Capability

Name and runtime instructions match the included Python revenue-calculation script. No unrelated binaries, env vars, or config paths are requested. Minor metadata gaps (no human-readable description/homepage) reduce provenance but do not contradict capability.

Instruction Scope

SKILL.md limits actions to gathering pricing inputs, selecting a strategy, running scripts/revenue-calc.py, and producing tables/reports. It does not instruct reading unrelated files, accessing system credentials, or sending data to external endpoints.

Install Mechanism

No install spec — instruction-only plus small local scripts. No downloads, package installs, or archive extraction are specified.

Credentials

No environment variables, credentials, or config paths are required. The code operates on provided inputs and prints JSON; it does not access secrets or external services.

Persistence & Privilege

always is false and the skill does not request persistent system-wide configuration. It contains only local scripts and reference/docs; no privileged or persistent behaviour is requested.

Assessment

This skill is internally consistent and appears to just run local Python math to project revenue. Before installing, review the small scripts (scripts/revenue-calc.py and scripts/example.py) yourself to confirm they match your expectations (they do in this package). Note the package has no homepage or owner metadata beyond an ID—if provenance or maintainer trust matters for you, ask for source/author info. As always, run unknown code in a safe environment and avoid feeding sensitive credentials or real production data to a new skill until you’ve validated its behavior.

Workflow

1. Gather Inputs: Users/mo, price ($/user/task), conv rate (%), churn (%), costs (% compute).
2. Select Strategy: 1=API Sales, 2=Marketplace, 3=White-label, 4=Affiliates.
3. Calculate: Monthly/annual rev, net profit. Use scripts/revenue-calc.py for models.
4. Output: Table + sensitivity (e.g., +/-20% users) + next steps.
5. Sensitivity: Test scenarios (low/med/high).

Quick Example

Input: Strategy 2, 100 users, $10/mo, 80% conv, 10% churn, 20% costs. Output: Monthly $800, Annual $8,640 net.

Strategies Pricing Defaults (ref/pricing-models.md)

• Sub: $9-99/mo
• Per-task: $0.01-1
• Usage: $0.001/token
• Affiliate: 5-20%

Resources

scripts/revenue-calc.py

Exec for precise calcs (input JSON → output JSON/table).

references/pricing-models.md

Full tables/examples.

assets/report-template.md

Copy for formatted outputs.